title: EMG signal morphology in essential tremor and Parkinson's disease.
abstract: The aim of this work was to differentiate patients with essential tremor from patients with Parkinson's disease. The electromyographic signal from the biceps brachii muscle was measured during isometric tension from 17 patients with essential tremor, 35 patients with Parkinson's disease, and 40 healthy controls. The EMG signals were high pass filtered and divided to smaller segments from which histograms were calculated using 200 histogram bins. EMG signal histogram shape was analysed with a feature dimension reduction method, the principal component analysis, and the shape parameters were used to differentiate between different patient groups. The height of the histogram and the side difference between left and right hand were the best discriminators between essential tremor and Parkinson's disease groups. With this method, it was possible to discriminate 13/17 patients with essential tremor from 26/35 patients with Parkinson's disease and 14/17 patients with essential tremor from 29/40 healthy controls.
authors.forename: V
authors.initials: V
authors.lastname: Ruonala
authors.forename: A
authors.initials: A
authors.lastname: Meigal
authors.forename: S M
authors.initials: SM
authors.lastname: Rissanen
authors.forename: O
authors.initials: O
authors.lastname: Airaksinen
authors.forename: M
authors.initials: M
authors.lastname: Kankaanpaa
authors.forename: P A
authors.initials: PA
authors.lastname: Karjalainen
mesh_terms: D000200:Action Potentials; D003937:Diagnosis, Differential; D016002:Discriminant Analysis; D004576:Electromyography; D020329:Essential Tremor / Q000175:diagnosis*; D006225:Hand / Q000502:physiology; D006801:Humans; D010300:Parkinson Disease / Q000175:diagnosis*; D025341:Principal Component Analysis; D012720:Severity of Illness Index; D012815:Signal Processing, Computer-Assisted